Senior Machine Learning Engineer, Digital Twin Platform

We're transforming the grocery industry

At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers.

Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.

Instacart is a Flex First team

There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work.

Overview

The Digital Twin Platform team at Instacart is on a mission to understand exactly what is on store shelves at all times — bringing the precision and depth of a smart warehouse to every local grocery store across North America. Inventory estimates power some of the most critical products at Instacart, from search to logistics, and this team sits at the center of it all. Operating like a startup within a larger company, the team drives the end-to-end shelf data supply chain: ingesting data from retail partners, actively collecting novel inventory observations, developing sophisticated models, and integrating those outputs into live products at scale.

We are looking for a Senior Machine Learning Engineer to help build the next generation of platforms for understanding, observing, and predicting inventory levels and in-store stocking dynamics in real time. In this role, you will develop machine learning models and deploy them into production systems, working in close collaboration with software engineers, computer vision engineers, product leads, and data scientists. If you're motivated by technically complex, high-impact problems and want to see your work shape how millions of people experience grocery shopping, this is the role for you.

You can read more about some of the work this team is doing here:

Introducing New Enterprise AI Solutions to Democratize AI for Grocers of All Sizes

Instacart Acquires Arpalus to Advance Real-Time Shelf Intelligence

About the Job

Design, develop, and deploy machine learning models that power real-time understanding of in-store inventory levels and shelf stocking dynamics across thousands of retail locations at scale.

Own the full ML lifecycle — from problem framing and data exploration through model training, evaluation, and production deployment — with a focus on quality, reliability, and measurable business impact.

Collaborate cross-functionally with software engineers, computer vision engineers, data scientists, and product leads to bring cutting-edge technologies to the team and drive new product innovation.

Contribute to building and evolving the core infrastructure of the Digital Twin Platform, including systems that ingest data from retail partners and actively collect novel inventory observations to feed the modeling pipeline.

Help define the technical direction of an expanding modeling practice on a high-performance team that operates with startup speed — expect ambiguity, changing priorities, and the opportunity to make a significant mark on a problem space that is core to Instacart's business.

About You

Minimum Qualifications

5+ years of experience developing and deploying machine learning models in production environments.

Strong proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.

Demonstrated experience with large-scale data pipelines and working with structured and unstructured data at scale.

Experience with cloud infrastructure (AWS, GCP, or Azure) and familiarity with ML platform tooling for model training, versioning, and serving.

Bachelor's degree or higher in Computer Science, Machine Learning, Statistics, or a related technical field, or equivalent practical experience.